A GIS-based analytical framework for evaluating the effect of COVID-19 on the restaurant industry with big data  

作　　者：Siqin Wang Ruomei Wang Xiao Huang Zhenlong Li Shuming Bao 

机构地区：[1]School of Earth and Environmental Sciences,University of Queensland,Brisbane,Queensland,Australia [2]Graduate School of Interdisciplinary Information Studies,University of Tokyo,Tokyo,Japan [3]Department of Geosciences,University of Arkansas,Ann Arbor,Michigan,USA [4]Geoinformation and Big Data Research Laboratory,Department of Geography,University of South Carolina,South Carolina,USA [5]China Data Institute,Michigan,USA

出　　处：《Big Earth Data》2023年第1期37-58,共22页地球大数据（英文）

基　　金：This study was funded by the National Science Foundation(Grant#2028791).

摘　　要：COVID-19 cripples the restaurant industry as a crucial socioeconomic sector that contributes immensely to the global economy.However,what the current literature less explored is to quantify the effect of COVID-19 on restaurant visitation and revenue at different spatial scales,as well as its relationship with the neighborhood character-istics of customers’origins.Based on the Point of Interest(POI)measures derived from SafeGraph data providing mobility records of 45 million cell phone users in the US,our study takes Lower Manhattan,New York City,as the pilot study,and aims to examine 1)the change of restaurant visitations and revenue in the period prior to and after the COVID-19 outbreak,2)the areas where restaurant customers live,and 3)the association between the neighborhood characteristics of these areas and lost customers.By doing so,we provide a geographic information system-based analytical frame-work integrating the big data mining,web crawling techniques,and spatial-economic modelling.Our analytical framework can be implemented to estimate the broader effect of COVID-19 on other industries and can be augmented in a financially monitoring manner in response to future pandemics or public emergencies.

关 键 词：COVID-19 pandemic effect restaurant visitation human mobility New York City 

分 类 号：F719.3[经济管理—产业经济] TP311[自动化与计算机技术—计算机软件与理论]